Multifaceted design optimization for superomniphobic surfaces

Panter, J. R. ORCID:, Gizaw, Y. and Kusumaatmaja, H. (2019) Multifaceted design optimization for superomniphobic surfaces. Science Advances, 5 (6). ISSN 2375-2548

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Superomniphobic textures are at the frontier of surface design for vast arrays of applications. Despite recent substantial advances in fabrication methods for reentrant and doubly reentrant microstructures, design optimization remains a major challenge. We overcome this in two stages. First, we develop readily generalizable computational methods to systematically survey three key wetting properties: contact angle hysteresis, critical pressure, and minimum energy wetting barrier. For each, we uncover multiple competing mechanisms, leading to the development of quantitative models and correction of inaccurate assumptions in prevailing models. Second, we combine these analyses simultaneously, demonstrating the power of this strategy by optimizing structures that are designed to overcome challenges in two emerging applications: membrane distillation and digital microfluidics. As the wetting properties are antagonistically coupled, this multifaceted approach is essential for optimal design. When large surveys are impractical, we show that genetic algorithms enable efficient optimization, offering speedups of up to 10,000 times.

Item Type: Article
Additional Information: Funding Information: We would like to thank C. Semprebon, I. Liu, and E. Xi for useful discussions and C. M. Jones for updating the energy minimization software. We thank P&G and EPSRC (EP/P007139/1) for funding. Publisher Copyright: Copyright © 2019 The Authors,
Uncontrolled Keywords: general ,/dk/atira/pure/subjectarea/asjc/1000
Faculty \ School: Faculty of Science > School of Engineering
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Depositing User: LivePure Connector
Date Deposited: 14 Sep 2022 15:30
Last Modified: 20 Oct 2022 19:33
DOI: 10.1126/sciadv.aav7328

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